Before revision:  Tree-boosting shows excellent predictive accuracy on many data sets, but potential drawbacks are that it assumes conditional independence of samples, produces discontinuous predictions for,  and it can have difficulty with high-cardinality categorical variables.
After revision:  Tree-boosting shows excellent predictive accuracy on many data sets, but potential drawbacks are that it assumes conditional independence of samples, produces discontinuous predictions for, e.g., spatial data, and it can have difficulty with high-cardinality categorical variables.