Artificial neurons are based on biological neurons (see figure 1). As you might have learned in high school, a biological neuron fires off signals when it encounters sufficient stimuli. It is able to pass these signals as output to other neurons. Artificial neurons are very similar. It receives one or more input signals and, when activated, passes an output signal to other neurons.
Figure 1. Biological and artificial neuron (Source: https://www.deloitte.com/)
Examining artificial neurons in Figure 2 more closely shows that each input has a certain weight attached to it. This weight indicates the significance of the input with regard to the task that the artificial neural network is trying to learn. The product of all inputs and their respective weights are combined and passed as a total input to the neuron.