Confidence of this particual prediction
If I understand your question correctly, then this is not possible for a "generic" model. For a generic model, you can only use generic methods. One of the most generic would be bootstrap sampling. In this scenario, you take your model and train it on different bootstrap samples and derive confidence intervals from the distribution of these predictions. 

However, it sounds like you are looking for a method that does not require training. In this case, you would need to use models from which confidence intervals can be derived directly based on the model assumptions, such as linear regression, Gaussian processes or Bayesian models.