The F1 score is a measure of a test's accuracy, balancing precision and recall to provide a single metric that reflects a model's performance, especially useful in cases of imbalanced class distribution. It is the harmonic mean of precision and recall, ensuring that both false positives and false negatives are accounted for in evaluating the model's effectiveness.