Parameter reduction is a strategy used in computational and statistical models to simplify complex systems by decreasing the number of parameters, thereby enhancing computational efficiency and reducing the risk of overfitting. This technique is crucial in high-dimensional data analysis, where it helps in improving model interpretability without significantly sacrificing accuracy.