**Apache Airflow version**: 2.0.1
**Kubernetes version**: v1.19.7
**Executor**: KubernetesExecutor

**What happened**:

If you have a worker that gets stuck in pending forever, say with a missing volume mount, the task will stay in the queued state forever. Nothing is applying a timeout on it actually being able to start.

**What you expected to happen**:

Eventually the scheduler will notice that the worker hasn't progressed past pending after a given amount of time and will mark it as a failure.

**How to reproduce it**:
```python
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.utils.dates import days_ago
from kubernetes.client import models as k8s


default_args = {
    "owner": "airflow",
}

with DAG(
    dag_id="pending",
    default_args=default_args,
    schedule_interval=None,
    start_date=days_ago(2),
) as dag:
    BashOperator(
        task_id="forever_pending",
        bash_command="date; sleep 30; date",
        executor_config={
            "pod_override": k8s.V1Pod(
                spec=k8s.V1PodSpec(
                    containers=[
                        k8s.V1Container(
                            name="base",
                            volume_mounts=[
                                k8s.V1VolumeMount(mount_path="/foo/", name="vol")
                            ],
                        )
                    ],
                    volumes=[
                        k8s.V1Volume(
                            name="vol",
                            persistent_volume_claim=k8s.V1PersistentVolumeClaimVolumeSource(
                                claim_name="missing"
                            ),
                        )
                    ],
                )
            ),
        },
    )
```


**Anything else we need to know**:
Related to:

* #15149 (This is reporting that these pending pods don't get deleted via "Mark Failed")
* #14556 (This handles when these pending pods get deleted and is already fixed)

airflow/jobs/scheduler_job.py
session.query(TI)
                .filter(TI.state != State.SUCCESS, TI.execution_date.in_(sla_dates), TI.dag_id == dag.dag_id)
                .all()
            )
            blocking_tis: List[TI] = []
            for ti in fetched_tis:
                if ti.task_id in dag.task_ids:
                    ti.task = dag.get_task(ti.task_id)
                    blocking_tis.append(ti)
                else:
                    session.delete(ti)
                    session.commit()
            task_list = "\n".join([sla.task_id + ' on ' + sla.execution_date.isoformat() for sla in slas])
            blocking_task_list = "\n".join(
                [ti.task_id + ' on ' + ti.execution_date.isoformat() for ti in blocking_tis]
            )
            
            
            email_sent = False
            notification_sent = False
            if dag.sla_miss_callback:
                
                self.log.info('Calling SLA miss callback')
                try:
                    dag.sla_miss_callback(dag, task_list, blocking_task_list, slas, blocking_tis)
                    notification_sent = True
                except Exception:  
                    self.log.exception("Could not call sla_miss_callback for DAG %s", dag.dag_id)
            email_content = f"""\
            Here's a list of tasks that missed their SLAs: