A residual in regression is the difference between what the model predicts and what actually happened. It represents the error in the model's prediction for a specific observation. If the model predicts a value and the actual value is different, the residual shows how far off the prediction was. Smaller residuals indicate a better fit, meaning the model is doing a good job predicting the outcomes.