Which of the following statements is false in relation to the type of machine learning models?

Classification and Regression are supervised machine learning techniques. Clustering is an unsupervised machine learning technique.

Supervised learning model requires that the target $($or label$)$ variable is present in your training dataset where as Unsupervised learning model will not have a target $($or label$)$ variable in training dataset and and must find patterns, structures, or relationships within the data without explicit guidance.

A Classification model is used when the goal is to categorize data into classes, while regression model is employed when the objective is to predict a continuous numeric value. The choice between them depends on the nature of the problem and the type$($ categorical or continuous numeric value$)$ of output required.

I would use a regression model when target variable $($or lables$)$ in the dataset includes values as $0,1,2$ and $3$ repersenting the Red, Blue, Yellow and Green colors.