**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)

tests/executors/test_kubernetes_executor.py
)
            assert not executor.task_queue.empty()
            task = executor.task_queue.get_nowait()
            _, _, expected_executor_config, expected_pod_template_file = task
            
            assert expected_executor_config.metadata.labels == {'release': 'stable'}
            assert expected_pod_template_file == template_file
            self.kubernetes_executor.kube_scheduler.run_next(task)
            mock_run_pod_async.assert_called_once_with(
                k8s.V1Pod(
                    api_version="v1",
                    kind="Pod",
                    metadata=k8s.V1ObjectMeta(
                        name=mock.ANY,
                        namespace="default",
                        annotations={
                            'dag_id': 'dag',
                            'execution_date': execution_date.isoformat(),
                            'task_id': 'task',
                            'try_number': '1',
                        },
                        labels={
                            'airflow-worker': '5',
                            'airflow_version': mock.ANY,
                            'dag_id': 'dag',
                            'execution_date': datetime_to_label_safe_datestring(execution_date),
                            'kubernetes_executor': 'True',
                            'mylabel': 'foo',
                            'release': 'stable',
                            'task_id': 'task',