What does the CountVectorizer output X represent in the code snippet below? from sklearn.feature$\_$extraction.text import CountVectorizer # Sample text data data $=["$Machine learning is fascinating.", "Natural language processing and machine learning are closely linked."$]$ # Initialise the CountVectorizer vectorizer $=$ CountVectorizer$()$ # Fit and transform the data X $=$ vectorizer.fit$\_$transform$($data$)$ # Get the feature names feature$\_$names $=$ vectorizer.get$\_$feature$\_$names$\_$out$()$ A$,$ A list of all words used across the documents. B$,$The count of unique words in each document. C$,$ The frequency of each word in each document. D$,$ A binary indication of whether a word appears in a document or not.