### 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)

"""Render k8s pod yaml"""
        from kubernetes.client.api_client import ApiClient
        from airflow.kubernetes.kube_config import KubeConfig
        from airflow.kubernetes.kubernetes_helper_functions import create_pod_id  
        from airflow.kubernetes.pod_generator import PodGenerator
        kube_config = KubeConfig()
        pod = PodGenerator.construct_pod(
            dag_id=self.dag_id,
            run_id=self.run_id,
            task_id=self.task_id,
            map_index=self.map_index,
            date=None,
            pod_id=create_pod_id(self.dag_id, self.task_id),
            try_number=self.try_number,
            kube_image=kube_config.kube_image,
            args=self.command_as_list(),
            pod_override_object=PodGenerator.from_obj(self.executor_config),
            scheduler_job_id="0",
            namespace=kube_config.executor_namespace,
            base_worker_pod=PodGenerator.deserialize_model_file(kube_config.pod_template_file),
        )
        settings.pod_mutation_hook(pod)
        sanitized_pod = ApiClient().sanitize_for_serialization(pod)
        return sanitized_pod
    def get_email_subject_content(