Cost function, loss function, or error function are used interchangeably by practitioners. Each is used to define and measure the error of a model. The objective for the ML algorithm is to minimize the loss from the dataset.

Some of the examples of cost function are square loss that is used in linear regression, hinge loss that is used in support vector machines and 0/1 loss used to measure accuracy in classification algorithms.