### Apache Airflow version

2.2.0 (latest released)

### Operating System

Mac

### Versions of Apache Airflow Providers

_No response_

### Deployment

Other Docker-based deployment

### Deployment details

_No response_

### What happened

Getting an exception when returning None from next_dagrun_info in a custom timetable. The timetable protocol says that when None is returned a DagRun will not happen but right now it throws an exception.

Exception:
```
Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 623, in _execute
    self._run_scheduler_loop()
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 704, in _run_scheduler_loop
    num_queued_tis = self._do_scheduling(session)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 787, in _do_scheduling
    callback_to_run = self._schedule_dag_run(dag_run, session)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 1039, in _schedule_dag_run
    self._update_dag_next_dagruns(dag, dag_model, active_runs)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 930, in _update_dag_next_dagruns
    data_interval = dag.get_next_data_interval(dag_model)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/models/dag.py", line 629, in get_next_data_interval
    return self.infer_automated_data_interval(dag_model.next_dagrun)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/models/dag.py", line 671, in infer_automated_data_interval
    raise ValueError(f"Not a valid timetable: {self.timetable!r}")
ValueError: Not a valid timetable: <my_timetables.workday_timetable.WorkdayTimetable object at 0x7f42b1f02430>
```

### What you expected to happen

DagRun to not happen.

### How to reproduce

Create a custom timetable and return None in next_dagrun_info after a few DagRuns are created by that timetable

### 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)

tests/models/test_dag.py
"""
        Test if the schedule_interval will be auto aligned with the start_date
        such that if the start_date coincides with the schedule the first
        execution_date will be start_date, otherwise it will be start_date +
        interval.
        """
        dag = DAG(
            dag_id='test_scheduler_auto_align_1',
            start_date=timezone.datetime(2016, 1, 1, 10, 10, 0),
            schedule_interval="4 5 * * *",
        )
        DummyOperator(task_id='dummy', dag=dag, owner='airflow')
        next_info = dag.next_dagrun_info(None)
        assert next_info and next_info.logical_date == timezone.datetime(2016, 1, 2, 5, 4)
        dag = DAG(
            dag_id='test_scheduler_auto_align_2',
            start_date=timezone.datetime(2016, 1, 1, 10, 10, 0),
            schedule_interval="10 10 * * *",
        )
        DummyOperator(task_id='dummy', dag=dag, owner='airflow')
        next_info = dag.next_dagrun_info(None)
        assert next_info and next_info.logical_date == timezone.datetime(2016, 1, 1, 10, 10)
    def test_next_dagrun_after_not_for_subdags(self):
        """
        Test the subdags are never marked to have dagruns created, as they are
        handled by the SubDagOperator, not the scheduler
        """
        def subdag(parent_dag_name, child_dag_name, args):