Machine-to-machine (M2M) communication has become an integral part of various industries, facilitating efficient data exchange and enabling autonomous decision-making processes. However, the proliferation of interconnected devices has brought about unprecedented security challenges. Conventional cryptographic methods may not be sufficient to protect sensitive data in the face of rapidly evolving cyber threats. To address this issue, a novel approach combining blockchain technology and deep quantum computing has been proposed to enhance the security and privacy of M2M communication. This paper presents an advanced blockchain-enabled deep quantum computing model designed to safeguard machine-to-machine communication from potential cyber threats. At the core of the model is a quantum key distribution (QKD) protocol, which enables the secure establishment of cryptographic keys between communicating devices. To ensure the scalability and immutability of the M2M communication network, a blockchain framework is integrated into the system. Additionally, the model incorporates deep learning techniques to bolster the security infrastructure further. In this paper we introduce an innovative solution to address the security challenges in machine-to-machine communication. By integrating advanced quantum computing, blockchain technology, and deep learning, the proposed model establishes a robust and secure framework that ensures the confidentiality, integrity, and authenticity of M2M data exchanges.