Cochlear implant users have limited ability to understand speech in noisy conditions. Signal processing methods to address this issue that use multiple microphones typically use beamforming to perform noise reduction. However, the effectiveness of the beamformer is diminished as the number of interfering noises increases and the acoustic environment becomes more diffuse. A multi-microphone noise reduction algorithm that aims to address this issue is presented in this study. The algorithm uses spatial filtering to estimate the signal-to-noise ratio (SNR) and attenuates time-frequency elements that have poor SNR. The algorithm was evaluated by measuring intelligibility of speech embedded in 4-talker babble where the interfering talkers were spatially separated and changed location during the test. Twelve cochlear implant users took part in the evaluation, which demonstrated a significant mean improvement of 4.6 dB (standard error 0.4, P < 0.001) in speech reception threshold compared to an adaptive beamformer. The results suggest that a substantial improvement in performance can be gained for cochlear implant users in noisy environments where the noise is spatially separated from the target speech.