Temporal Anomaly Detection involves identifying patterns in time-series data that deviate from expected behavior, which can indicate unusual events or changes in system dynamics. It is crucial for applications such as fraud detection, network security, and predictive maintenance, where timely identification of anomalies can prevent significant losses or failures.