### 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)

self,
        verbose: bool = True,
        ignore_all_deps: bool = False,
        ignore_depends_on_past: bool = False,
        ignore_task_deps: bool = False,
        ignore_ti_state: bool = False,
        mark_success: bool = False,
        test_mode: bool = False,
        job_id: str | None = None,
        pool: str | None = None,
        external_executor_id: str | None = None,
        session: Session = NEW_SESSION,
    ) -> 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
        :param ignore_all_deps: Ignore all of the non-critical dependencies, just runs
        :param ignore_depends_on_past: Ignore depends_on_past DAG attribute
        :param ignore_task_deps: Don't check the dependencies of this TaskInstance's task
        :param ignore_ti_state: Disregards previous task instance state
        :param mark_success: Don't run the task, mark its state as success
        :param test_mode: Doesn't record success or failure in the DB
        :param job_id: Job (BackfillJob / LocalTaskJob / SchedulerJob) ID