In recent years Machine Learning techniques have proven to reduce energy consumption when applied to cloud computing systems. Reinforcement Learning provides a promising solution for the reduction of energy consumption, while maintaining a high quality of service for customers. We present a novel single agent Reinforcement Learning approach for the selection of virtual machines, creating a new energy efficiency practice for data centres. Our dynamic Reinforcement Learning virtual machine selection policy learns to choose the optimal virtual machine to migrate from an over-utilised host. Our experiment results show that a learning agent has the abilities to reduce energy consumption and decrease the number of migrations when compared to a state-of-the-art approach.