**Description**
The `airflow.models.baseoperator.chain()` is a very useful and convenient way to add sequential task dependencies in DAGs.  This function has [recently been updated](https://github.com/apache/airflow/issues/16635) to support `BaseOperator` and `XComArgs` but should also be able to support `Labels` as well.

**Use case / motivation**
Users who create tasks via the `@task` decorator will not be able to use the `chain()` function to apply sequential dependencies that do not share an `XComArg` implicit dependency with a `Label`.  This use case can occur when attempting to chain multiple branch labels and the next sequential task.

With the new update (yet to be released), users will receive the following exception when attempting to chain an `XComArg` and `Label`:

```bash
TypeError: Chain not supported between instances of <class 'airflow.utils.edgemodifier.EdgeModifier'> and <class 'airflow.models.xcom_arg.XComArg'>
```


**Are you willing to submit a PR?**
Absolutely. 🚀 

**Related Issues**
None

airflow/models/baseoperator.py
if start_date and not isinstance(start_date, datetime):
            self.log.warning("start_date for %s isn't datetime.datetime", self)
        elif start_date:
            self.start_date = timezone.convert_to_utc(start_date)
        self.end_date = end_date
        if end_date:
            self.end_date = timezone.convert_to_utc(end_date)
        if not TriggerRule.is_valid(trigger_rule):
            raise AirflowException(
                "The trigger_rule must be one of {all_triggers},"
                "'{d}.{t}'; received '{tr}'.".format(
                    all_triggers=TriggerRule.all_triggers(),
                    d=dag.dag_id if dag else "",
                    t=task_id,
                    tr=trigger_rule,
                )
            )
        self.trigger_rule = trigger_rule
        self.depends_on_past = depends_on_past
        self.wait_for_downstream = wait_for_downstream
        if wait_for_downstream:
            self.depends_on_past = True
        if retries is not None and not isinstance(retries, int):
            try:
                parsed_retries = int(retries)
            except (TypeError, ValueError):
                raise AirflowException(f"'retries' type must be int, not {type(retries).__name__}")
            self.log.warning("Implicitly converting 'retries' for %s from %r to int", self, retries)
            retries = parsed_retries
        self.retries = retries