### Apache Airflow version

2.7.3

### What happened

We are facing an issue using Kubernetes Executor where `process_watcher_task` that gets None state and is pushed to `result_queue`. On fetching the state from queue in `kubernetes_executor.py` it's passed to `_change_state` and if the state is None then state is fetched from database which when is also None due to some reason the `TaskInstanceState(state)` throws `ValueError` which is caught in the exception and the result is again added to the queue causing scheduler to go into infinite loop trying to set state. We need to restart the scheduler to make it run. If state is None database query too then we shouldn't set the state or to catch `ValueError` instead of generic exception handling to not retry by pushing the same result to queue. The validation was introduced by this change https://github.com/apache/airflow/commit/9556d6d5f611428ac8a3a5891647b720d4498ace#diff-11bb8713bf2f01502e66ffa91136f939cc8445839517187f818f044233414f7eR459


https://github.com/apache/airflow/blob/5d74ffb32095d534866f029d085198bc783d82c2/airflow/providers/cncf/kubernetes/executors/kubernetes_executor_utils.py#L453-L465

https://github.com/apache/airflow/blob/f3ddefccf610833dc8d6012431f372f2af03053c/airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py#L379-L393

https://github.com/apache/airflow/blob/5d74ffb32095d534866f029d085198bc783d82c2/airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py#L478-L485

### What you think should happen instead

scheduler should not retry infinitely

### How to reproduce

We are not sure of the exact scenario where this reproducible. We tried running a task that returns an event which k8s returns None in rare case when pod is deleted or killed and also delete the task instance to make sure db query also returns None but we are not able to consistently get to the case that causes this.

### Operating System

Ubuntu

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] 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)

pod: k8s.V1Pod,
        tis_to_flush_by_key: dict[TaskInstanceKey, k8s.V1Pod],
    ) -> None:
        """
        Patch existing pod so that the current KubernetesJobWatcher can monitor it via label selectors.
        :param kube_client: kubernetes client for speaking to kube API
        :param pod: V1Pod spec that we will patch with new label
        :param tis_to_flush_by_key: TIs that will be flushed if they aren't adopted
        """
        if TYPE_CHECKING:
            assert self.scheduler_job_id
        self.log.info("attempting to adopt pod %s", pod.metadata.name)
        ti_key = annotations_to_key(pod.metadata.annotations)
        if ti_key not in tis_to_flush_by_key:
            self.log.error("attempting to adopt taskinstance which was not specified by database: %s", ti_key)
            return
        new_worker_id_label = self._make_safe_label_value(self.scheduler_job_id)
        from kubernetes.client.rest import ApiException
        try:
            kube_client.patch_namespaced_pod(
                name=pod.metadata.name,
                namespace=pod.metadata.namespace,
                body={"metadata": {"labels": {"airflow-worker": new_worker_id_label}}},
            )
        except ApiException as e:
            self.log.info("Failed to adopt pod %s. Reason: %s", pod.metadata.name, e)
            return
        del tis_to_flush_by_key[ti_key]
        self.running.add(ti_key)
    def _adopt_completed_pods(self, kube_client: client.CoreV1Api) -> None: