Genetic Programming (GP) is an Evolutionary Algorithm commonly used to evolve computer programs in order to solve a particular task. Therefore, GP has been used to tackle different problems like classification and regression. In this work, the capabilities of GP in other types of problems are explored, particularly the feature selection problem. For this purpose, GP is applied to a set of benchmark problems, and, then, compared to other algorithms. The results obtained show that GP is competitive against the other algorithms, and in addition to this, no modifications are needed to perform the feature extraction task.