Choosing the correct algorithm depends on the data and the desired outcome. Random Forest is better for dealing with nonlinear relationships, so if the data does not exhibit a linear relationship, Random Forest may be a better choice. On the other hand, if the data does have a strong linear relationship, Linear Regression will likely outperform Random Forest. Ultimately, it depends on the dataset's model type and the desired outcome.