Virtual reality (VR) imaging is 360 degrees, which requires a large bandwidth for video transmission. To address this challenge, tile-based streaming has been proposed to deliver only the focused part of the video instead of the entire one. However, the impact of cybersickness, akin to motion sickness, on tile selection in VR has not been explored. In this paper, we investigate Multi-user Tile Streaming with Cybersickness Control (MTSCC) in an adaptive 360(degrees) video streaming system with multicast and cybersickness alleviation. We propose a novel m(2)-competitive online algorithm that utilizes Individual Sickness Indicator (ISI) and Bitrate Restriction Indicator (BRI) to evaluate user cybersickness tendency and network bandwidth efficiency. Moreover, we introduce the Video Loss Indicator (VLI) and Quality Variance Indicator (QVI) to assess video quality loss and quality difference between tiles. We also propose a multi-armed bandit (MAB) algorithm with confidence bound-based reward (video quality) and cost (cybersickness) estimation. The algorithm learns the weighting factor of each user's cost to slow down cybersickness accumulation for users with high cybersickness tendencies. We prove that the algorithm converges to an optimal solution over time. According to simulation with real network settings, our proposed algorithms outperform baselines in terms of video quality and cybersickness accumulation.