An anomaly threshold is a predefined value used to distinguish between normal and anomalous data points in a dataset, often employed in anomaly detection systems. Setting the appropriate threshold is crucial as it balances the trade-off between false positives and false negatives, thereby impacting the system's sensitivity and specificity.