### 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)

else:
            if self.state == State.QUEUED:
                
                self._try_number += 1
            self.state = State.UP_FOR_RETRY
            email_for_state = operator.attrgetter("email_on_retry")
            callback = task.on_retry_callback if task else None
            callback_type = "on_retry"
        self._log_state("Immediate failure requested. " if force_fail else "")
        if task and email_for_state(task) and task.email:
            try:
                self.email_alert(error, task)
            except Exception:
                self.log.exception("Failed to send email to: %s", task.email)
        if callback and context:
            self._run_finished_callback(callback, context, callback_type)
        if not test_mode:
            session.merge(self)
            session.flush()
    def is_eligible_to_retry(self):
        """Is task instance is eligible for retry"""
        if self.state == State.RESTARTING:
            
            
            return True
        if not getattr(self, "task", None):
            
            return self.try_number <= self.max_tries
        return self.task.retries and self.try_number <= self.max_tries
    def get_template_context(