the cause of dimensionality has to do with the different phenomena that comes up whenever data is to be analyzed or organized in high dimensional spaces which do not happen in low dimensional spaces. This curse can be explained simply as having error increase just as there are increases in the number of features. when the features we have is more than the observations, it could cause the model to be overfitted.
