The lambda parameter is a hyperparameter used in various machine learning algorithms to control the trade-off between fitting the training data and keeping the model complexity low, often used in regularization techniques like Lasso and Ridge regression. It helps prevent overfitting by penalizing large coefficients, thereby promoting simpler models that generalize better to unseen data.