True Negative Rate (TNR), also known as specificity, measures the proportion of actual negatives correctly identified by a binary classification test. It is crucial for evaluating the performance of models, particularly in scenarios where distinguishing true negatives from false positives is important, such as in medical diagnostics to avoid unnecessary treatments.