### 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)

if not _is_further_mapped_inside(upstream, common_ancestor):
            return ancestor_map_index
        
        
        further_count = ti_count // ancestor_ti_count
        map_index_start = ancestor_map_index * further_count
        return range(map_index_start, map_index_start + further_count)
def _find_common_ancestor_mapped_group(node1: Operator, node2: Operator) -> MappedTaskGroup | None:
    """Given two operators, find their innermost common mapped task group."""
    if node1.dag is None or node2.dag is None or node1.dag_id != node2.dag_id:
        return None
    parent_group_ids = {g.group_id for g in node1.iter_mapped_task_groups()}
    common_groups = (g for g in node2.iter_mapped_task_groups() if g.group_id in parent_group_ids)
    return next(common_groups, None)
def _is_further_mapped_inside(operator: Operator, container: TaskGroup) -> bool:
    """Whether given operator is *further* mapped inside a task group."""
    if isinstance(operator, MappedOperator):
        return True
    task_group = operator.task_group
    while task_group is not None and task_group.group_id != container.group_id:
        if isinstance(task_group, MappedTaskGroup):
            return True
        task_group = task_group.parent_group
    return False
TaskInstanceStateType = Tuple[TaskInstanceKey, str]
class SimpleTaskInstance: