### 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)

airflow/models/dag.py
f_sig.apply_defaults()
            
            dag_id = dag_bound_args.arguments.get('dag_id', f.__name__)
            dag_bound_args.arguments['dag_id'] = dag_id
            
            with DAG(*dag_bound_args.args, **dag_bound_args.kwargs) as dag_obj:
                
                if f.__doc__:
                    dag_obj.doc_md = f.__doc__
                
                
                f_kwargs = {}
                for name, value in f_sig.arguments.items():
                    f_kwargs[name] = dag_obj.param(name, value)
                
                back = sys._getframe().f_back
                dag_obj.fileloc = back.f_code.co_filename if back else ""
                
                f(**f_kwargs)
            
            return dag_obj
        return factory
    return wrapper
STATICA_HACK = True
globals()['kcah_acitats'[::-1].upper()] = False
if STATICA_HACK:  
    from airflow.models.serialized_dag import SerializedDagModel
    DagModel.serialized_dag = relationship(SerializedDagModel)
class DagContext: