Break Into Tensor

When I was looking through some fantastic articles by data scientist columnists, I came across into the concept of tensor and I tell myself, it is the time to look under the hood and figure it out

What is this ‘tensor’?

## Defining the loss function
loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(logits=predicted_y,labels=input_y)) \
        + regularizer_rate*(tf.reduce_sum(tf.square(bias_0)) + tf.reduce_sum(tf.square(bias_1)))

I quote this code snippet from this blog by Aayush Agrawal.
So we know tensor flow is a great library from google. What does it solve exactly and here what does this reduce_mean mean at all?
The reduce_meanfunction here gives the average of the elements of a tensor object in a fixed dimension.

How is it relevant to Machine Learning and Deep Learning?