The difference between linear and nonlinear in machine learning lies in how data relationships are modeled. Linear models assume a straight-line connection, while nonlinear models capture more complex patterns. Non-linear Machine learning optimization enhances model accuracy by finding optimal parameters for these intricate, real-world relationships.