### 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)

"""Create the mapped task instances for mapped task.
        :raise NotMapped: If this task does not need expansion.
        :return: The newly created mapped task instances (if any) in ascending
            order by map index, and the maximum map index value.
        """
        from sqlalchemy import func, or_
        from airflow.models.baseoperator import BaseOperator
        from airflow.models.mappedoperator import MappedOperator
        from airflow.models.taskinstance import TaskInstance
        from airflow.settings import task_instance_mutation_hook
        if not isinstance(self, (BaseOperator, MappedOperator)):
            raise RuntimeError(f"cannot expand unrecognized operator type {type(self).__name__}")
        try:
            total_length: int | None = self.get_mapped_ti_count(run_id, session=session)
        except NotFullyPopulated as e:
            
            
            
            if not self.dag or not self.dag.partial:
                self.log.error(
                    "Cannot expand %r for run %s; missing upstream values: %s",
                    self,
                    run_id,
                    sorted(e.missing),
                )
            total_length = None