### Apache Airflow version

2.2.0 (latest released)

### Operating System

Container-Optimized OS with Containerd (cos_containerd) - GKE

### Versions of Apache Airflow Providers

_No response_

### Deployment

Astronomer

### Deployment details

_No response_

### What happened

I went to clear a successful task instance that is using a Deferred operator, and noticed it immediately went into a state of successful. The Operator is designed to run a trigger that will wait 1 minute from approximately task start. Upon investigation, I did not see the following in the second run's task log: `{taskinstance.py:1332} INFO - Pausing task as DEFERRED.`.

### What you expected to happen

I would expect the task to once again go into a state of deferred for approx. 1 minute and then succeed.

### How to reproduce

Run the following DAG. Once a task instance is successful, clear it, and see the task fail. This confirms `ti.next_method` was not cleared, as `execute` did not rerun and reset `execute_try_number`. `execute` did not rerun, as `ti.next_method` was not cleared.

```
from datetime import datetime

from airflow import DAG
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.triggers.testing import SuccessTrigger


class RetryOperator(BaseOperator):
    def execute(self, context):
        ti = context["ti"]
        next_method = ti.next_method
        try_number = ti.try_number

        self.log.info(
            f"In `execute`: try_number: {try_number}, next_method {next_method}."
        )

        self.defer(
            trigger=SuccessTrigger(),
            method_name="next",
            kwargs={"execute_try_number": try_number},
        )

    def next(self, context, execute_try_number, event=None):
        ti = context["ti"]
        next_method = ti.next_method
        try_number = ti.try_number

        self.log.info(
            f"In `next`: try_number: {try_number}, next_method {next_method}, execute_try_number: {execute_try_number}."
        )

        if execute_try_number != try_number:
            raise AirflowException("`execute` wasn't run during clear!")

        return None  # Success!


with DAG(
    "triggerer_clear", schedule_interval=None, start_date=datetime(2021, 10, 20)
) as dag:
    RetryOperator(task_id="clear")
```

### Anything else

I believe this is due to `ti.next_method` (and `ti.next_method_kwargs`) not being cleared after a task has completed. A similar issue was raised in https://github.com/apache/airflow/issues/18146.

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/models/taskinstance.py
pool: Optional[str] = None,
        external_executor_id: Optional[str] = None,
        session=None,
    ) -> bool:
        """
        Checks dependencies and then sets state to RUNNING if they are met. Returns
        True if and only if state is set to RUNNING, which implies that task should be
        executed, in preparation for _run_raw_task
        :param verbose: whether to turn on more verbose logging
        :type verbose: bool
        :param ignore_all_deps: Ignore all of the non-critical dependencies, just runs
        :type ignore_all_deps: bool
        :param ignore_depends_on_past: Ignore depends_on_past DAG attribute
        :type ignore_depends_on_past: bool
        :param ignore_task_deps: Don't check the dependencies of this TaskInstance's task
        :type ignore_task_deps: bool
        :param ignore_ti_state: Disregards previous task instance state
        :type ignore_ti_state: bool
        :param mark_success: Don't run the task, mark its state as success
        :type mark_success: bool
        :param test_mode: Doesn't record success or failure in the DB
        :type test_mode: bool
        :param job_id: Job (BackfillJob / LocalTaskJob / SchedulerJob) ID
        :type job_id: str
        :param pool: specifies the pool to use to run the task instance
        :type pool: str
        :param external_executor_id: The identifier of the celery executor
        :type external_executor_id: str
        :param session: SQLAlchemy ORM Session
        :type session: Session