The correct answer is D. Recurrent Neural Network (RNN).
RNNs are a type of artificial neural network that are well-suited for tasks that involve sequential data, such as text classification, language translation, and speech recognition. They work by having a feedback loop that allows them to remember information from previous inputs, which is essential for these types of tasks.
Random Forests are a type of ensemble learning algorithm that uses a collection of decision trees to make predictions. They are often used for classification and regression tasks, but they can also be used for text classification.
Support Vector Machines (SVMs) are a type of supervised learning algorithm that can be used for both classification and regression tasks. They work by finding a hyperplane in a high-dimensional space that separates the data into two classes.
Naive Bayes is a type of probabilistic machine learning algorithm that is often used for text classification. It works by assuming that the features of a document are independent of each other, which can be a good approximation for many types of text data.
In conclusion, RNNs are the best choice for text classification, language translation, and speech recognition because they are specifically designed for tasks that involve sequential data.