### Apache Airflow version

2.2.0b2 (beta snapshot)

### Operating System

ubuntu 20.04

### Versions of Apache Airflow Providers

n/a

### Deployment

Virtualenv installation

### Deployment details

pip install /path/to/airflow/src

### What happened

Given any DAG initialized with: `schedule_interval=None`

Run `airflow dags test mydagname $(date +%Y-%m-%d)` and get an error:

```
INFO - No run dates were found for the given dates and dag interval.
```

This behavior changed in https://github.com/apache/airflow/pull/15397, it used to trigger a backfill dagrun at the given date.

### What you expected to happen

I expected a backfill dagrun with the given date, regardless of whether it fit into the `schedule_interval`.

If AIP-39 made that an unrealistic expectation, then I'd hope for some way to define unscheduled dags which can still be tested from the command line (which, so far as I know, is the fastest way to iterate on a DAG.).

As it is, I keep changing `schedule_interval` back and forth depending on whether I want to iterate via `astro dev start` (which tolerates `None` but does superfluous work if the dag is scheduled) or via `airflow dags test ...` (which doesn't tolerate `None`).

### How to reproduce

Initialize a DAG with: `schedule_interval=None` and run it via `airflow dags test mydagname $(date +%Y-%m-%d)`

### 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/jobs/backfill_job.py
if runs:
            run = runs[0]
            if run.state == State.RUNNING:
                respect_dag_max_active_limit = False
        else:
            run = None
        
        
        if respect_dag_max_active_limit and current_active_dag_count >= dag.max_active_runs:
            return None
        run = run or dag.create_dagrun(
            execution_date=run_date,
            data_interval=dagrun_info.data_interval,
            start_date=timezone.utcnow(),
            state=State.RUNNING,
            external_trigger=False,
            session=session,
            conf=self.conf,
            run_type=DagRunType.BACKFILL_JOB,
            creating_job_id=self.id,
        )
        
        run.dag = dag
        
        run.state = State.RUNNING
        run.run_type = DagRunType.BACKFILL_JOB
        run.verify_integrity(session=session)
        return run
    @provide_session
    def _task_instances_for_dag_run(self, dag_run, session=None):