### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Our scheduler started failing with this trace:

  File "/usr/local/lib/python3.9/site-packages/airflow/models/taskinstance.py", line 1187, in get_failed_dep_statuses
    for dep_status in dep.get_dep_statuses(self, session, dep_context):
  File "/usr/local/lib/python3.9/site-packages/airflow/ti_deps/deps/base_ti_dep.py", line 95, in get_dep_statuses
    yield from self._get_dep_statuses(ti, session, dep_context)
  File "/usr/local/lib/python3.9/site-packages/airflow/ti_deps/deps/not_in_retry_period_dep.py", line 47, in _get_dep_statuses
    next_task_retry_date = ti.next_retry_datetime()
  File "/usr/local/lib/python3.9/site-packages/airflow/models/taskinstance.py", line 1243, in next_retry_datetime
    return self.end_date + delay
OverflowError: date value out of range

We found a dag with a large # of retries and exponential backoff will trigger this date error and take down the entire scheduler. The workaround is to force a max_delay setting. 

The bug is here:
https://github.com/apache/airflow/blob/2.3.3/airflow/models/taskinstance.py#L1243

The current version seems to use the same code:
https://github.com/apache/airflow/blob/main/airflow/models/taskinstance.py#L1147


### What you think should happen instead

There are a few solutions. Exponential backoff should probably require a max delay value.

At the very least, it shouldn't kill the scheduler.

### How to reproduce

Create dag with exponential delay and force it to retry until it overflows.

### Operating System

linux

### Versions of Apache Airflow Providers

_No response_

### Deployment

Astronomer

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] 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)

file_path: str | None = None,
        raw: bool = False,
        job_id: str | None = None,
        pool: str | None = None,
        cfg_path: str | None = None,
        map_index: int = -1,
    ) -> list[str]:
        """
        Generates the shell command required to execute this task instance.
        :param dag_id: DAG ID
        :param task_id: Task ID
        :param run_id: The run_id of this task's DagRun
        :param mark_success: Whether to mark the task as successful
        :param ignore_all_deps: Ignore all ignorable dependencies.
            Overrides the other ignore_* parameters.
        :param ignore_depends_on_past: Ignore depends_on_past parameter of DAGs
            (e.g. for Backfills)
        :param ignore_task_deps: Ignore task-specific dependencies such as depends_on_past
            and trigger rule
        :param ignore_ti_state: Ignore the task instance's previous failure/success
        :param local: Whether to run the task locally
        :param pickle_id: If the DAG was serialized to the DB, the ID
            associated with the pickled DAG
        :param file_path: path to the file containing the DAG definition
        :param raw: raw mode (needs more details)
        :param job_id: job ID (needs more details)
        :param pool: the Airflow pool that the task should run in
        :param cfg_path: the Path to the configuration file
        :return: shell command that can be used to run the task instance
        """