The widespread use of unmanned aerial vehicles (UAVs) in low-altitude airspace has raised significant safety and security concerns, motivating the development of reliable non-cooperative UAV surveillance technologies. Integrated sensing and communication (ISAC), enabled by multiple-input multiple-output (MIMO) architectures and orthogonal frequency-division multiplexing (OFDM) waveforms, has emerged as a promising paradigm for leveraging cellular infrastructure to support large-scale sensing without additional hardware deployment. This paper presents the first comprehensive survey dedicated to MIMO OFDM-enabled ISAC for low-altitude non-cooperative UAV surveillance, where the targeted UAVs do not intentionally assist the monitoring system through dedicated signaling or prior coordinate sharing. We first analyze the unique propagation characteristics of low-altitude UAV sensing, including severe clutter, rapid channel variations, and mixed near/far-field effects, and discuss corresponding waveform design principles. We then systematically review existing MIMO OFDM-enabled UAV surveillance techniques along four key dimensions: ISAC system modeling and network optimization, UAV detection and tracking algorithms under single and networked base station (BS) architectures, UAV identification techniques based on micro-Doppler and learning-based approaches, and experimental validations and practical field trials. Subsequently, we summarize open challenges such as sensing under severe clutter and multipath, data scarcity for identification, cooperative multi-BS fusion, and real-world deployment constraints. Finally, we outline promising future research directions toward 5G-Advanced (5G-A) and 6G-enabled low-altitude surveillance systems.