### 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)

tests/cli/commands/test_dag_command.py
"None",
            "None",
        ]
        for i, dag_id in enumerate(dag_ids):
            dag = self.dagbag.dags[dag_id]
            
            dag.create_dagrun(
                run_type=DagRunType.SCHEDULED,
                execution_date=now,
                start_date=now,
                state=State.FAILED,
            )
            
            args = self.parser.parse_args(['dags', 'next-execution', dag_id])
            with contextlib.redirect_stdout(io.StringIO()) as temp_stdout:
                dag_command.dag_next_execution(args)
                out = temp_stdout.getvalue()
            assert expected_output[i] in out
            
            args = self.parser.parse_args(['dags', 'next-execution', dag_id, '--num-executions', '2'])
            with contextlib.redirect_stdout(io.StringIO()) as temp_stdout:
                dag_command.dag_next_execution(args)
                out = temp_stdout.getvalue()
            assert expected_output_2[i] in out
        
        with create_session() as session:
            dr = session.query(DagRun).filter(DagRun.dag_id.in_(dag_ids))
            dr.delete(synchronize_session=False)
    @conf_vars({('core', 'load_examples'): 'true'})
    def test_cli_report(self):